计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2013年
10期
228-231
,共4页
语音编码%线谱频率%转换分裂矢量量化%卡尔曼滤波
語音編碼%線譜頻率%轉換分裂矢量量化%卡爾曼濾波
어음편마%선보빈솔%전환분렬시량양화%잡이만려파
speech coding%line-spectrum frequency%Switch Split Vector Quantization%Kalman filter
针对LSP参数在转换分裂矢量量化(Switch Split Vector Quantization,SSVQ)中未能充分利用子矢量间相关性的不足,提出了一种LSP参数SSVQ的卡尔曼后滤波增强方法.该方法在解码端利用卡尔曼滤波器来进一步发掘子矢量间和连续帧矢量间的相关性,并结合SSVQ中分类的转换来自适应地调整卡尔曼滤波器的参数.实验结果表明,方法可在SSVQ的平均频谱误差为0.9~1.0 dB时进一步减少0.01~0.02 dB.
針對LSP參數在轉換分裂矢量量化(Switch Split Vector Quantization,SSVQ)中未能充分利用子矢量間相關性的不足,提齣瞭一種LSP參數SSVQ的卡爾曼後濾波增彊方法.該方法在解碼耑利用卡爾曼濾波器來進一步髮掘子矢量間和連續幀矢量間的相關性,併結閤SSVQ中分類的轉換來自適應地調整卡爾曼濾波器的參數.實驗結果錶明,方法可在SSVQ的平均頻譜誤差為0.9~1.0 dB時進一步減少0.01~0.02 dB.
침대LSP삼수재전환분렬시량양화(Switch Split Vector Quantization,SSVQ)중미능충분이용자시량간상관성적불족,제출료일충LSP삼수SSVQ적잡이만후려파증강방법.해방법재해마단이용잡이만려파기래진일보발굴자시량간화련속정시량간적상관성,병결합SSVQ중분류적전환래자괄응지조정잡이만려파기적삼수.실험결과표명,방법가재SSVQ적평균빈보오차위0.9~1.0 dB시진일보감소0.01~0.02 dB.
In this paper, a Kalman post-filter approach is proposed to improve the performance of the Switch Split Vector Quan-tization(SSVQ)of LSF parameters. In the proposed approach, the correlations between the successive and sub LSF vectors are recovered by the Kalman filter in the decoder end. The parameters of the Kalman filter are adjusted according to the classifica-tion results in the first step of the SSVQ. Experimental results show that the proposed approach can further reduce the average spectral distortion of 0.01~0.02 dB when the average spectral distortion of the SSVQ is around 0.9~1.0 dB.
